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Dentro del SOC

Minimizing the REvil Impact Delivered via Kaseya Servers

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08
Jul 2021
08
Jul 2021
Ransomware group REvil recently infiltrated Managed Service Providers for 1,500+ companies. See how Darktrace's autonomous response protected customer data.

As the USA prepared for a holiday weekend ahead of the Fourth of July, the ransomware group REvil were leveraging a vulnerability in Kaseya software to attack Managed Service Providers (MSPs) and their downstream customers. At least 1,500 companies appear to have been affected, even ones with no direct relationship to Kaseya.

At the time of writing, it appears that a zero-day vulnerability was used to gain access to the Kaseya VSA servers, before deploying ransomware on the endpoints managed by those VSA servers. This modus operandi vastly differs from previous ransomware campaigns which have traditionally been human-operated, direct intrusions.

The analysis below offers Darktrace’s insights into the campaign by looking at a real-life example. It highlights how Self-Learning AI detected the ransomware attack, and how Antigena protected customer data on the network from being encrypted.

Dissecting REvil ransomware from the network perspective

Antigena detected the first signs of ransomware on the network as soon as encryption had begun. The graphic below illustrates the start of the ransomware encryption over SMB shares. When the graphic was taken, the attack was happening live and had never been seen before. As it was a novel threat, Darktrace stopped the network encryption without any static signatures or rules.

Figure 1: Darktrace detects encryption from the infected device

The ransomware began to take action at 11:08:32, shown by the ‘SMB Delete Success’ from the infected laptop to an SMB server. While the laptop sometimes reads files on that SMB server, it never deletes these types of files on this particular file share, so Darktrace detected this activity as new and unusual.

Simultaneously, the infected laptop created the ransom note ‘943860t-readme.txt’. Again, the ‘SMB Write Success’ to the SMB server was new activity – and crucially, Darktrace did not look for a static string or a known ransom note. Instead – by previously learning the ‘normal’ behavior of every entity, peer group, and the overall enterprise – it identified that the activity was unusual and new for this organization and device.

By detecting and correlating these subtle anomalies, Darktrace identified this as the earliest stages of ransomware encryption on the network and Antigena took immediate action.

Figure 2: Snapshot of Antigena’s actions

Antigena took two precise steps:

  1. Enforce ‘pattern of life’ for five minutes: This prevented the infected laptop from making any connections that were new or unusual. In this case, it prevented any further new SMB encryption activity.
  2. Quarantine device for 24 hours: Usually, Antigena would not take such drastic action, but it was clear that this activity closely resembled ransomware behavior, so Antigena decided to quarantine the device on the network completely to prevent it from doing any further damage.

For several minutes, the infected laptop kept trying to connect to other internal devices via SMB to continue the encryption activity. It was blocked by Antigena at every stage, limiting the spread of the attack and mitigating any damage posed via the network encryption.

Figure 3: End of the attack

On a technical level, Antigena delivered the blocking mechanisms via integrations with native security controls such as existing firewalls, or by taking action itself to disrupt the connections.

The below graphic shows the ‘pattern of life’ for all network connections for the infected laptop. The three red dots represent Darktrace’s detections and pinpoint the exact moment in time when REvil ransomware was installed on the laptop. The graphic also shows an abrupt stop to all network communication as Antigena quarantined the device.

Figure 4: Network connections from the compromised laptop

Attacks will always get in

During the incident, part of the encryption happened locally on the endpoint device, which Darktrace had no visibility over. Furthermore, the Internet-facing Kaseya VSA server that was initially compromised was not visible to Darktrace in this case.

Nevertheless, Self-Learning AI detected the infection as soon as it reached the network. This shows the importance of being able to defend against active ransomware within the enterprise. Organizations cannot rely solely on a single layer of defense to keep threats out. An attacker will always – eventually – breach your environment. Defense therefore needs to change its approach towards detecting and mitigating damage once an adversary is inside.

Many cyber-attacks succeed in bypassing endpoint controls and begin to spread aggressively in corporate environments. Autonomous Response can provide resilience in such cases, even for novel campaigns and new strains of malware.

Thanks to Self-Learning AI, ransomware from the REvil attack could not perform any encryption over the network, and files available on that network were saved. This included the organization’s critical file servers which did not have Kaseya installed and thus did not receive the initial payload via the malicious update directly. By interrupting the attack as it happened, Antigena prevented thousands of files on network shares from being encrypted.

Further observations

Data exfiltration

In contrast to other REvil intrusions Darktrace has caught in the past, no data exfiltration has been observed. This is interesting as it differs from the general trend this last year where cyber-criminal groups generally focus more on the exfiltration of data to hold their victims to ransom, in response to companies becoming better with backups.

Bitcoin

REvil has demanded a total payment of $70 million in Bitcoin. For a group that tries to maximize their profits, this seems odd for two reasons:

  1. How do they expect a single entity to collect $70 million from potentially thousands of affected organizations? They must be aware of the massive logistical challenges behind this, even if they do expect Kaseya to act as a focal point for collecting the money.
  2. Since DarkSide lost access to most of the Colonial Pipeline ransom, ransomware groups have shifted to demanding payments in Monero rather than Bitcoin. Monero appears to be more difficult to track for law enforcement agencies. The fact REvil are using Bitcoin, a more traceable cryptocurrency, appears counter-productive to their usual goal of maximizing profits.

Ransomware-as-a-Service (RaaS)

Darktrace also noticed that other, more traditional ‘big game hunting’ REvil ransomware operations took place over the same weekend. This is not surprising as REvil is running a RaaS model, so it is likely some affiliate groups continued their regular big game hunting attacks while the Kaseya supply chain attack was underway.

Unpredictable is not undefendable

The weekend of the Fourth of July experienced major supply chain attacks against Kaseya and separately, against California-based distributor Synnex. Threats are coming from every direction – leveraging zero-days, social engineering tactics, and other advanced tools.

The case study above demonstrates how self-learning technology detects such attacks and minimizes the damage. It functions as a crucial part of defense-in-depth when other layers – such as endpoint protection, threat intelligence or known signatures and rules – fail to detect unknown threats.

The attack happened in milliseconds, faster than any human security team could react. Autonomous Response has proven invaluable in outpacing this new generation of machine-speed threats. It keeps thousands of organizations safe around the world, around the clock, stopping an attack every second.

Darktrace model detections

  • Compromise / Ransomware / Suspicious SMB Activity
  • Compromise / Ransomware / Suspicious SMB File Extension
  • Compromise / Ransomware / Ransom or Offensive Words Written to SMB
  • Compromise / Ransomware / Ransom or Offensive Words Read from SMB
DENTRO DEL SOC
Darktrace son expertos de talla mundial en inteligencia de amenazas, caza de amenazas y respuesta a incidentes, y proporcionan apoyo al SOC las 24 horas del día a miles de clientes de Darktrace en todo el mundo. Inside the SOC está redactado exclusivamente por estos expertos y ofrece un análisis de los ciberincidentes y las tendencias de las amenazas, basado en la experiencia real sobre el terreno.
AUTOR
SOBRE EL AUTOR
Max Heinemeyer
Chief Product Officer

Max is a cyber security expert with over a decade of experience in the field, specializing in a wide range of areas such as Penetration Testing, Red-Teaming, SIEM and SOC consulting and hunting Advanced Persistent Threat (APT) groups. At Darktrace, Max is closely involved with Darktrace’s strategic customers & prospects. He works with the R&D team at Darktrace, shaping research into new AI innovations and their various defensive and offensive applications. Max’s insights are regularly featured in international media outlets such as the BBC, Forbes and WIRED. Max holds an MSc from the University of Duisburg-Essen and a BSc from the Cooperative State University Stuttgart in International Business Information Systems.

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Email

How to Protect your Organization Against Microsoft Teams Phishing Attacks

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21
May 2024

The problem: Microsoft Teams phishing attacks are on the rise

Around 83% of Fortune 500 companies rely on Microsoft Office products and services1, with Microsoft Teams and Microsoft SharePoint in particular emerging as critical platforms to the business operations of the everyday workplace. Researchers across the threat landscape have begun to observe these legitimate services being leveraged more and more by malicious actors as an initial access method.

As Teams becomes a more prominent feature of the workplace many employees rely on it for daily internal and external communication, even surpassing email usage in some organizations. As Microsoft2 states, "Teams changes your relationship with email. When your whole group is working in Teams, it means you'll all get fewer emails. And you'll spend less time in your inbox, because you'll use Teams for more of your conversations."

However, Teams can be exploited to send targeted phishing messages to individuals either internally or externally, while appearing legitimate and safe. Users might receive an external message request from a Teams account claiming to be an IT support service or otherwise affiliated with the organization. Once a user has accepted, the threat actor can launch a social engineering campaign or deliver a malicious payload. As a primarily internal tool there is naturally less training and security awareness around Teams – due to the nature of the channel it is assumed to be a trusted source, meaning that social engineering is already one step ahead.

Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)
Figure 1: Screenshot of a Microsoft Teams message request from a Midnight Blizzard-controlled account (courtesy of Microsoft)

Microsoft Teams Phishing Examples

Microsoft has identified several major phishing attacks using Teams within the past year.

In July 2023, Microsoft announced that the threat actor known as Midnight Blizzard – identified by the United States as a Russian state-sponsored group – had launched a series of phishing campaigns via Teams with the aim of stealing user credentials. These attacks used previously compromised Microsoft 365 accounts and set up new domain names that impersonated legitimate IT support organizations. The threat actors then used social engineering tactics to trick targeted users into sharing their credentials via Teams, enabling them to access sensitive data.  

At a similar time, threat actor Storm-0324 was observed sending phishing lures via Teams containing links to malicious SharePoint-hosted files. The group targeted organizations that allow Teams users to interact and share files externally. Storm-0324’s goal is to gain initial access to hand over to other threat actors to pursue more dangerous follow-on attacks like ransomware.

For a more in depth look at how Darktrace stops Microsoft Teams phishing read our blog: Don’t Take the Bait: How Darktrace Keeps Microsoft Teams Phishing Attacks at Bay

The market: Existing Microsoft Teams security solutions are insufficient

Microsoft’s native Teams security focuses on payloads, namely links and attachments, as the principal malicious component of any phishing. These payloads are relatively straightforward to detect with their experience in anti-virus, sandboxing, and IOCs. However, this approach is unable to intervene before the stage at which payloads are delivered, before the user even gets the chance to accept or deny an external message request. At the same time, it risks missing more subtle threats that don’t include attachments or links – like early stage phishing, which is pure social engineering – or completely new payloads.

Equally, the market offering for Teams security is limited. Security solutions available on the market are always payload-focused, rather than taking into account the content and context in which a link or attachment is sent. Answering questions like:

  • Does it make sense for these two accounts to speak to each other?
  • Are there any linguistic indicators of inducement?

Furthermore, they do not correlate with email to track threats across multiple communication environments which could signal a wider campaign. Effectively, other market solutions aren’t adding extra value – they are protecting against the same types of threats that Microsoft is already covering by default.

The other aspect of Teams security that native and market solutions fail to address is the account itself. As well as focusing on Teams threats, it’s important to analyze messages to understand the normal mode of communication for a user, and spot when a user’s Teams activity might signal account takeover.

The solution: How Darktrace protects Microsoft Teams against sophisticated threats

With its biggest update to Darktrace/Email ever, Darktrace now offers support for Microsoft Teams. With that, we are bringing the same AI philosophy that protects your email and accounts to your messaging environment.  

Our Self-Learning AI looks at content and context for every communication, whether that’s sent in an email or Teams message. It looks at actual user behavior, including language patterns, relationship history of sender and recipient, tone and payloads, to understand if a message poses a threat. This approach allows Darktrace to detect threats such as social engineering and payloadless attacks using visibility and forensic capabilities that Microsoft security doesn’t currently offer, as well as early symptoms of account compromise.  

Unlike market solutions, Darktrace doesn’t offer a siloed approach to Teams security. Data and signals from Teams are shared across email to inform detection, and also with the wider Darktrace ActiveAI security platform. By correlating information from email and Teams with network and apps security, Darktrace is able to better identify suspicious Teams activity and vice versa.  

Interested in the other ways Darktrace/Email augments threat detection? Read our latest blog on how improving the quality of end-user reporting can decrease the burden on the SOC. To find our more about Darktrace's enduring partnership with Microsoft, click here.

References

[1] Essential Microsoft Office Statistics in 2024

[2] Microsoft blog, Microsoft Teams and email, living in harmony, 2024

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About the author
Carlos Gray
Product Manager

Blog

Dentro del SOC

Don’t Take the Bait: How Darktrace Keeps Microsoft Teams Phishing Attacks at Bay

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20
May 2024

Social Engineering in Phishing Attacks

Faced with increasingly cyber-aware endpoint users and vigilant security teams, more and more threat actors are forced to think psychologically about the individuals they are targeting with their phishing attacks. Social engineering methods like taking advantage of the human emotions of their would-be victims, pressuring them to open emails or follow links or face financial or legal repercussions, and impersonating known and trusted brands or services, have become common place in phishing campaigns in recent years.

Phishing with Microsoft Teams

The malicious use of the popular communications platform Microsoft Teams has become widely observed and discussed across the threat landscape, with many organizations adopting it as their primary means of business communication, and many threat actors using it as an attack vector. As Teams allows users to communicate with people outside of their organization by default [1], it becomes an easy entry point for potential attackers to use as a social engineering vector.

In early 2024, Darktrace/Apps™ identified two separate instances of malicious actors using Microsoft Teams to launch a phishing attack against Darktrace customers in the Europe, the Middle East and Africa (EMEA) region. Interestingly, in this case the attackers not only used a well-known legitimate service to carry out their phishing campaign, but they were also attempting to impersonate an international hotel chain.

Despite these attempts to evade endpoint users and traditional security measures, Darktrace’s anomaly detection enabled it to identify the suspicious phishing messages and bring them to the customer’s attention. Additionally, Darktrace’s autonomous response capability, was able to follow-up these detections with targeted actions to contain the suspicious activity in the first instance.

Darktrace Coverage of Microsoft Teams Phishing

Chats Sent by External User and Following Actions by Darktrace

On February 29, 2024, Darktrace detected the presence of a new external user on the Software-as-a-Service (SaaS) environment of an EMEA customer for the first time. The user, “REDACTED@InternationalHotelChain[.]onmicrosoft[.]com” was only observed on this date and no further activities were detected from this user after February 29.

Later the same day, the unusual external user created its first chat on Microsoft Teams named “New Employee Loyalty Program”. Over the course of around 5 minutes, the user sent 63 messages across 21 different chats to unique internal users on the customer’s SaaS platform. All these chats included the ‘foreign tenant user’ and one of the customer’s internal users, likely in an attempt to remain undetected. Foreign tenant user, in this case, refers to users without access to typical internal software and privileges, indicating the presence of an external user.

Darktrace’s detection of unusual messages being sent by a suspicious external user via Microsoft Teams.
Figure 1: Darktrace’s detection of unusual messages being sent by a suspicious external user via Microsoft Teams.
Advanced Search results showing the presence of a foreign tenant user on the customer’s SaaS environment.
Figure 2: Advanced Search results showing the presence of a foreign tenant user on the customer’s SaaS environment.

Darktrace identified that the external user had connected from an unusual IP address located in Poland, 195.242.125[.]186. Darktrace understood that this was unexpected behavior for this user who had only previously been observed connecting from the United Kingdom; it further recognized that no other users within the customer’s environment had connected from this external source, thereby deeming it suspicious. Further investigation by Darktrace’s analyst team revealed that the endpoint had been flagged as malicious by several open-source intelligence (OSINT) vendors.

External Summary highlighting the rarity of the rare external source from which the Teams messages were sent.
Figure 3: External Summary highlighting the rarity of the rare external source from which the Teams messages were sent.

Following Darktrace’s initial detection of these suspicious Microsoft Teams messages, Darktrace's autonomous response was able to further support the customer by providing suggested mitigative actions that could be applied to stop the external user from sending any additional phishing messages.

Unfortunately, at the time of this attack Darktrace's autonomous response capability was configured in human confirmation mode, meaning any autonomous response actions had to be manually actioned by the customer. Had it been enabled in autonomous response mode, it would have been able promptly disrupt the attack, disabling the external user to prevent them from continuing their phishing attempts and securing precious time for the customer’s security team to begin their own remediation procedures.

Darktrace autonomous response actions that were suggested following the ’Large Volume of Messages Sent from New External User’ detection model alert.
Figure 4: Darktrace autonomous response actions that were suggested following the ’Large Volume of Messages Sent from New External User’ detection model alert.

External URL Sent within Teams Chats

Within the 21 Teams chats created by the threat actor, Darktrace identified 21 different external URLs being sent, all of which included the domain "cloud-sharcpoint[.]com”. Many of these URLs had been recently established and had been flagged as malicious by OSINT providers [3]. This was likely an attempt to impersonate “cloud-sharepoint[.]com”, the legitimate domain of Microsoft SharePoint, with the threat actor attempting to ‘typo-squat’ the URL to convince endpoint users to trust the legitimacy of the link. Typo-squatted domains are commonly misspelled URLs registered by opportunistic attackers in the hope of gaining the trust of unsuspecting targets. They are often used for nefarious purposes like dropping malicious files on devices or harvesting credentials.

Upon clicking this malicious link, users were directed to a similarly typo-squatted domain, “InternatlonalHotelChain[.]sharcpoInte-docs[.]com”. This domain was likely made to appear like the SharePoint URL used by the international hotel chain being impersonated.

Redirected link to a fake SharePoint page attempting to impersonate an international hotel chain.
Figure 5: Redirected link to a fake SharePoint page attempting to impersonate an international hotel chain.

This fake SharePoint page used the branding of the international hotel chain and contained a document named “New Employee Loyalty Program”; the same name given to the phishing messages sent by the attacker on Microsoft Teams. Upon accessing this file, users would be directed to a credential harvester, masquerading as a Microsoft login page, and prompted to enter their credentials. If successful, this would allow the attacker to gain unauthorized access to a user’s SaaS account, thereby compromising the account and enabling further escalation in the customer’s environment.

Figure 6: A fake Microsoft login page that popped-up when attempting to open the ’New Employee Loyalty Program’ document.

This is a clear example of an attacker attempting to leverage social engineering tactics to gain the trust of their targets and convince them to inadvertently compromise their account. Many corporate organizations partner with other companies and well-known brands to offer their employees loyalty programs as part of their employment benefits and perks. As such, it would not necessarily be unexpected for employees to receive such an offer from an international hotel chain. By impersonating an international hotel chain, threat actors would increase the probability of convincing their targets to trust and click their malicious messages and links, and unintentionally compromising their accounts.

In spite of the attacker’s attempts to impersonate reputable brands, platforms, Darktrace/Apps was able to successfully recognize the malicious intent behind this phishing campaign and suggest steps to contain the attack. Darktrace recognized that the user in question had deviated from its ‘learned’ pattern of behavior by connecting to the customer’s SaaS environment from an unusual external location, before proceeding to send an unusually large volume of messages via Teams, indicating that the SaaS account had been compromised.

A Wider Campaign?

Around a month later, in March 2024, Darktrace observed a similar incident of a malicious actor impersonating the same international hotel chain in a phishing attacking using Microsoft Teams, suggesting that this was part of a wider phishing campaign. Like the previous example, this customer was also based in the EMEA region.  

The attack tactics identified in this instance were very similar to the previously example, with a new external user identified within the network proceeding to create a series of Teams messages named “New Employee Loyalty Program” containing a typo-squatted external links.

There were a few differences with this second incident, however, with the attacker using the domain “@InternationalHotelChainExpeditions[.]onmicrosoft[.]com” to send their malicious Teams messages and using differently typo-squatted URLs to imitate Microsoft SharePoint.

As both customers targeted by this phishing campaign were subscribed to Darktrace’s Proactive Threat Notification (PTN) service, this suspicious SaaS activity was promptly escalated to the Darktrace Security Operations Center (SOC) for immediate triage and investigation. Following their investigation, the SOC team sent an alert to the customers informing them of the compromise and advising urgent follow-up.

Conclusion

While there are clear similarities between these Microsoft Teams-based phishing attacks, the attackers here have seemingly sought ways to refine their tactics, techniques, and procedures (TTPs), leveraging new connection locations and creating new malicious URLs in an effort to outmaneuver human security teams and conventional security tools.

As cyber threats grow increasingly sophisticated and evasive, it is crucial for organizations to employ intelligent security solutions that can see through social engineering techniques and pinpoint suspicious activity early.

Darktrace’s Self-Learning AI understands customer environments and is able to recognize the subtle deviations in a device’s behavioral pattern, enabling it to effectively identify suspicious activity even when attackers adapt their strategies. In this instance, this allowed Darktrace to detect the phishing messages, and the malicious links contained within them, despite the seemingly trustworthy source and use of a reputable platform like Microsoft Teams.

Credit to Min Kim, Cyber Security Analyst, Raymond Norbert, Cyber Security Analyst and Ryan Traill, Threat Content Lead

Appendix

Darktrace Model Detections

SaaS Model

Large Volume of Messages Sent from New External User

SaaS / Unusual Activity / Large Volume of Messages Sent from New External User

Indicators of Compromise (IoCs)

IoC – Type - Description

https://cloud-sharcpoint[.]com/[a-zA-Z0-9]{15} - Example hostname - Malicious phishing redirection link

InternatlonalHotelChain[.]sharcpolnte-docs[.]com – Hostname – Redirected Link

195.242.125[.]186 - External Source IP Address – Malicious Endpoint

MITRE Tactics

Tactic – Technique

Phishing – Initial Access (T1566)

References

[1] https://learn.microsoft.com/en-us/microsoftteams/trusted-organizations-external-meetings-chat?tabs=organization-settings

[2] https://www.virustotal.com/gui/ip-address/195.242.125.186/detection

[3] https://www.virustotal.com/gui/domain/cloud-sharcpoint.com

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About the author
Min Kim
Cyber Security Analyst
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